One workspace. Every wholesale lender. Real explanations.
Brokers spend more time on portal logins than on borrowers. RateStack normalizes wholesale lender pricing into one workspace and one rule trace, so you can present three scenarios to a client in the time it takes to log into one vendor.
The broker pain is portal sprawl: each wholesale lender has their own login, their own UI conventions, their own LLPA spreadsheet. Reproducing a single borrower scenario across five lenders is a half-hour of clicking and copy-paste — and the result is a comparison your borrower will never see in a defensible form.
RateStack ingests wholesale lender ratesheets through email-in, portal automation, and scrape — same way it does correspondent-side ratesheets — and exposes them through one normalized interface. You set up your lender pack once; from then on, every quote runs against all of them in parallel.
Saved scenarios are first-class. Save the borrower, run any time, attach to the loan record. When the borrower's situation moves (rate locks, FICO update, downpayment change), one click reruns and the trace shows what changed.
Before vs. after
The shape of a day.
The same operating model, rebuilt around explicit pricing and a single audit log.
Before
Five lender portals, five logins, five spreadsheets to compare.
After
One pricing call, one normalized comparison, one trace that explains the order of finish.
Before
Saved scenarios live in the LO's spreadsheet (or their head).
After
Saved scenarios are first-class records with a one-click rerun and a per-version diff.
Before
When a wholesale lender's portal is down, you lose half a day.
After
Email-in + scrape ingestion keeps prices fresh even when the portal is unreachable; you find out when you log in, not when the LO calls.
Before
Borrower asks 'why is this option better?' and you wave at a number.
After
Drill-down on any quote shows the rule trace — investor, program, every adjustment, the combine strategy.
Capabilities, framed for you
The platform pieces you'll touch first.
All wholesale lenders, one screen
Add lenders to your pack; pricing runs against all of them in parallel.
Smart 1003
LOs only see the fields relevant to the loan type. DSCR, bank-statement, ITIN lanes all reflow.
Saved scenarios
Per-borrower, per-loan. One-click rerun. Default scenario per LO for fast iteration.
Quote drill-down
Open any quote, see every adjustment with rule id and ratesheet version.
Email-in + vendor profiles
Wholesale lenders email you ratesheet PDFs; we ingest, version, and activate. Named profiles for common shapes.
Exception Inbox
Lock drift, pricing anomalies, missed fills — triaged with AI-suggested resolution.
Onboarding
What week one looks like.
A pragmatic sequence — from sandbox to first signed quote.
- 1
Day 1: build the lender pack
Tell us your wholesale lender list. We pre-seed templates for the common ones; the rest land via your first ingestion.
- 2
Day 2: scenario migration
Top borrower scenarios become saved scenarios. Set defaults per LO.
- 3
Week 1: ingestion live
Email-in + portal automation pulls in your daily ratesheets. QC dashboard surfaces low-confidence mappings.
- 4
Week 2: LO training
Two 30-minute sessions get LOs up to speed; the workspace is intuitive enough that experienced LOs are productive day one.
- 5
Week 3: webhooks + CRM
Subscribe pricing.computed; route into your CRM. The correlationId joins quote → CRM record.
- 6
Production
Run RateStack as the primary pricing surface; keep portals as a fallback while you reconcile your first month.
I gave back two hours a day to my LOs by getting them off five portals. The trace closed half my compliance tickets in the first week.
Frequently asked
Specific to your operating model.
Do you have lender packs for our specific wholesale lenders?
We seed templates for the most common wholesale lenders and learn the rest the first time we see a sheet. Confidence below threshold raises a QC item; resolved mappings persist.
Can we keep our LOS?
Yes. RateStack runs alongside your LOS. Most brokers integrate via the loan import endpoint (MISMO 3.4 / ULAD / JSON) and webhooks.
What about lender-required disclosures?
Quotes carry a disclosures field that maps from each lender's required text. The drill-down surfaces them with the rest of the trace.
How do we handle pricing differences between LO and borrower-facing rates?
Comp + margin layers handle this. Borrower-facing pricing applies the org/entity/officer margin stack; the LO sees both the raw lender price and the borrower-facing price in the trace.
Can a single LO see only their borrowers?
Yes. RBAC includes a 'borrower visibility' scope that restricts to assigned LO; org admins can override.
Ready when you are
See mortgage brokers on RateStack.
Live demo with your real ratesheets, your real scenarios, and an honest read on whether the platform fits your team.